Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

2015 ◽  
pp. 3-20 ◽  
Author(s):  
Valentina Ivanova ◽  
Patrick Lambrix ◽  
Johan Åberg
Keyword(s):  
Large Scale ◽  
Ontology Alignment ◽  
User Support

scholarly journals Matching Biomedical Ontologies through Adaptive Multi-Modal Multi-Objective Evolutionary Algorithm

Biology ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1287
Author(s):  
Xingsi Xue ◽  
Pei-Wei Tsai ◽  
Yucheng Zhuang
Keyword(s):  
Evolutionary Algorithm ◽  
Large Scale ◽  
Biomedical Ontology ◽  
Biomedical Data ◽  
Biomedical Ontologies ◽  
Ontology Alignment ◽  
Multi Objective Optimization ◽  
Matching Problem ◽  
Multi Objective ◽  
Matching Techniques

To integrate massive amounts of heterogeneous biomedical data in biomedical ontologies and to provide more options for clinical diagnosis, this work proposes an adaptive Multi-modal Multi-Objective Evolutionary Algorithm (aMMOEA) to match two heterogeneous biomedical ontologies by finding the semantically identical concepts. In particular, we first propose two evaluation metrics on the alignment’s quality, which calculate the alignment’s statistical and its logical features, i.e., its f-measure and its conservativity. On this basis, we build a novel multi-objective optimization model for the biomedical ontology matching problem. By analyzing the essence of this problem, we point out that it is a large-scale Multi-modal Multi-objective Optimization Problem (MMOP) with sparse Pareto optimal solutions. Then, we propose a problem-specific aMMOEA to solve this problem, which uses the Guiding Matrix (GM) to adaptively guide the algorithm’s convergence and diversity in both objective and decision spaces. The experiment uses Ontology Alignment Evaluation Initiative (OAEI)’s biomedical tracks to test aMMOEA’s performance, and comparisons with two state-of-the-art MOEA-based matching techniques and OAEI’s participants show that aMMOEA is able to effectively determine diverse solutions for decision makers.

scholarly journals TraIT, Translational research IT bridging the valley of death in translational medicine

2020 ◽  
Author(s):  
Jan-Willem Boiten ◽  
Rita Azevedo ◽  
Kees van Bochove ◽  
Marinel Cavelaars ◽  
André Dekker ◽  
...  
Keyword(s):  
Translational Research ◽  
Translational Medicine ◽  
Large Scale ◽  
New Technology ◽  
Clinical Applications ◽  
User Support ◽  
User Community ◽  
On Line ◽  
Valley Of Death

Translating new technology and biological findings into clinical applications is hampered by insufficient translational research IT. The Dutch Translational research IT (TraIT) initiative organizes, deploys, and manages data and workflows in an on-line “office suite”, supplemented with efficient training and user support. TraIT has been adopted by a wide user community providing an excellent large-scale demonstrator for the nation-wide Health-RI initiative.

Semantic Mediation in MedPeer

2018 ◽  
pp. 2200-2220
Author(s):  
Naïma Souâd Ougouti ◽  
Haféda Belbachir ◽  
Youssef Amghar
Keyword(s):  
Data Integration ◽  
Large Scale ◽  
Distributed Data ◽  
Ontology Alignment ◽  
Challenging Problem ◽  
Integration System ◽  
Source Data ◽  
Data Integration System ◽  
Semantic Mediation ◽  
Global Similarity

Peer-to-Peer (P2P) infrastructure is an emerging paradigm that offers new opportunities for the development of large-scale distributed systems. This architecture combined with the new techniques introduced by semantic web as ontologies encouraged the emergence of new multi-source data integration possibilities for sharing information. A challenging problem in such systems is to find correspondences between concepts of their different ontologies. This is a necessary step before locating peers that are relevant with respect to a given query. In this paper, the authors propose a new ontology alignment method which deals with both linguistic and semantic characteristics of concepts and uses graph structure to explore multiple depth levels of neighborhood in calculation of semantic similarity which is the most important part of their global similarity measure. This function is implemented into their new P2P heterogeneous and distributed data integration system MedPeer.

Semantic Mediation in MedPeer

2017 ◽  
Vol 12 (1) ◽  
pp. 1-18
Author(s):  
Naïma Souâd Ougouti ◽  
Haféda Belbachir ◽  
Youssef Amghar
Keyword(s):  
Data Integration ◽  
Large Scale ◽  
Distributed Data ◽  
Graph Structure ◽  
Ontology Alignment ◽  
New Techniques ◽  
Source Data ◽  
Data Integration System ◽  
Semantic Mediation ◽  
Global Similarity

Peer-to-Peer (P2P) infrastructure is an emerging paradigm that offers new opportunities for the development of large-scale distributed systems. This architecture combined with the new techniques introduced by semantic web as ontologies encouraged the emergence of new multi-source data integration possibilities for sharing information. A challenging problem in such systems is to find correspondences between concepts of their different ontologies. This is a necessary step before locating peers that are relevant with respect to a given query. In this paper, the authors propose a new ontology alignment method which deals with both linguistic and semantic characteristics of concepts and uses graph structure to explore multiple depth levels of neighborhood in calculation of semantic similarity which is the most important part of their global similarity measure. This function is implemented into their new P2P heterogeneous and distributed data integration system MedPeer.

Large-Scale Ontology Alignment- An Extraction Based Method to Support Information System Interoperability

2019 ◽  
Vol 10 (2) ◽  
pp. 59-84
Author(s):  
Mourad Zerhouni ◽  
Sidi Mohamed Benslimane
Keyword(s):  
Large Scale ◽  
Web Applications ◽  
Comprehensive Evaluation ◽  
Alignment Algorithm ◽  
Alignment Method ◽  
Ontology Alignment ◽  
Determining Factors ◽  
Data Volume ◽  
System Interoperability ◽  
Multiple Ontologies

Ontology alignment is an important way of establishing interoperability between Semantic Web applications that use different but related ontologies. Ontology alignment is the process of identifying semantically equivalent entities from multiple ontologies. This is not always obvious because technical constraints such as data volume and execution time are determining factors in the choice of an alignment algorithm. Nowadays, partitioning and modularization are two main strategies for breaking down large ontologies into blocks or ontology modules respectively to align ontologies. This article proposes ONTEM as an effective alignment method for large-scale ontology based on the ontology entities extraction. This article conducts a comprehensive evaluation using the datasets of the OAEI 2018 campaign. The obtained results are promising, and they revealed that ONTEM is one of the most effective systems.

Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

1999 ◽  
Vol 173 ◽  
pp. 243-248
Author(s):  
D. Kubáček ◽  
A. Galád ◽  
A. Pravda
Keyword(s):  
Image Processing ◽  
Large Scale ◽  
Harvard College ◽  
Oak Ridge ◽  
Large Scale Structures ◽  
Short Period Comet ◽  
Short Period ◽  
Scale Structures ◽  
Harvard College Observatory ◽  
Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

Evolution of Large-Scale Coronal Structures

1994 ◽  
Vol 144 ◽  
pp. 29-33
Author(s):  
P. Ambrož
Keyword(s):  
Magnetic Field ◽  
Field Line ◽  
Large Scale ◽  
Coronal Magnetic Field ◽  
Source Surface ◽  
Solar Cycles ◽  
Characteristic Relationship ◽  
The Magnetic Field ◽  
Coronal Structures

AbstractThe large-scale coronal structures observed during the sporadically visible solar eclipses were compared with the numerically extrapolated field-line structures of coronal magnetic field. A characteristic relationship between the observed structures of coronal plasma and the magnetic field line configurations was determined. The long-term evolution of large scale coronal structures inferred from photospheric magnetic observations in the course of 11- and 22-year solar cycles is described.Some known parameters, such as the source surface radius, or coronal rotation rate are discussed and actually interpreted. A relation between the large-scale photospheric magnetic field evolution and the coronal structure rearrangement is demonstrated.

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